Jie Wang - Papers

  • Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction. Oral
    Zhanqiu Zhang, Jianyu Cai, Yongdong Zhang, and Jie Wang.
    AAAI 2020.

  • D-SPIDER-SFO: A Decentralized Optimization Algorithm with Faster Convergence Rate for Nonconvex Problems.
    Taoxing Pan, Jun Liu, and Jie Wang.
    AAAI 2020.

  • Deep Model-Based Reinforcement Learning via Estimated Uncertainty and Conservative Policy Optimization.
    Qi Zhou, Houqiang Li, and Jie Wang.
    AAAI 2020.

  • Two Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets.
    Jie Wang, Zhanqiu Zhang, and Jieping Ye.
    JMLR (in press, Aug. 2019).

  • Functional Annotation of Human Protein Coding Isoforms via Non-convex Multi-Instance Learning.
    Tingjin Luo, Weizhong Zhang, Shuang Qiu, Yang Yang, Dongyun Yi, Guangtao Wang, Jieping Ye, and Jie Wang.
    SIGKDD 2017.

  • The Simpler The Better: A Unified Approach to Predicting Original Taxi Demands on Large-Scale Online.
    Yongxin Tong, Yuqiang Chen, Zimu Zhou, Lei Chen, Jie Wang, Qiang Yang, and Jieping Ye.
    SIGKDD 2017.

  • Scaling Up Sparse Support Vector Machine by Simultaneous Feature and Sample Reduction.
    Weizhong Zhang, Bin Hong, Jieping Ye, Deng Cai, Xiaofei He, and Jie Wang.
    ICML 2017. [Code Download]

  • Parallel Lasso Screening for Big Data Optimization.
    Qingyang Li, Shuang Qiu, Shuiwang Ji, Jieping Ye, and Jie Wang.
    SIGKDD 2016.

  • A Multi-task Learning Formulation for Survival Analysis.
    Yan Li, Jie Wang, Jieping Ye, and Chandan Reddy.
    SIGKDD 2016.

  • Large-scale Collaborative Imaging Genetics Studies of Risk Genetic Factors for Alzheimer’s Disease Across Multiple Institutions.
    Qingyang Li, Tao Yang, Liang Zhan, Derrek Hibar, Neda Jahanshad, Yalin Wang, Jieping Ye, Paul Thompson, and Jie Wang.
    MICCAI 2016.

  • An Efficient Algorithm For Weak Hierarchical Lasso.
    Yashu Liu, Jie Wang, and Jieping Ye.
    ACM Transactions on Knowledge Discovery from Data.

  • New Asymptotic Analysis Method for Phase Field Models in Moving Boundary Problem with Surface Tension.
    Jie Wang and Xiaoqiang Wang.
    Discrete and Continuous Dynamical Systems - Series B.

  • Multi-Layer Feature Reduction for Tree Structured Group Lasso via Hierarchical Projection. Spotlight
    Jie Wang and Jieping Ye.
    NIPS 2015.

  • Safe Screening for Multi-Task Feature Learning with Multiple Data Matrices.
    Jie Wang and Jieping Ye.
    ICML 2015.

  • Detecting genetic risk factors for Alzheimer’s disease in whole genome sequence data via Lasso screening.
    Tao Yang, Jie Wang, Qian Sun, Derrek Paul Hibar, Neda Jahanshad, Li Liu, Yalin Wang, Liang Zhan, Paul Thompson, and Jieping Ye.
    IEEE International Symposium on Biomedical Imaging, 2015.

  • Fused Lasso Screening Rules via the Monotonicity of Subdifferentials.
    Jie Wang, Wei Fan, and Jieping Ye.
    IEEE Transactions on Pattern Analysis and Machine Intelligence, to appear.

  • Lasso Screening Rules via Dual Polytope Projection. (Improved version of the one accepted by NIPS 2013)
    Jie Wang, Peter Wonka, and Jieping Ye.
    Journal of Machine Learning Research, 16(May):1063−1101, 2015. [Code Download]

  • Two-Layer Feature Reduction for Sparse-Group Lasso via Decomposition of Convex Sets. Spotlight
    Jie Wang and Jieping Ye.
    NIPS 2014. [Code Download]

  • A Safe Screening Rule for Sparse Logistic Regression.
    Jie Wang, Jiayu Zhou, Jun Liu, Peter Wonka, and Jieping Ye.
    NIPS 2014.

  • An Efficient Algorithm for Weak Hierarchical Lasso. KDD'14 best student paper award
    Yashu Liu, Jie Wang, and Jieping Ye.
    SIGKDD 2014.

  • Scaling SVM and Least Absolute Deviations via Exact Data Reduction.
    Jie Wang, Peter Wonka, and Jieping Ye.
    ICML 2014.

  • A Highly Scalable Parallel Algorithm for Isotropic Total Variation Models.
    Jie Wang, Qingyang Li, Sen Yang, Wei Fan, Peter Wonka, and Jieping Ye.
    ICML 2014. [FAD Code Download]

  • Safe Screening with Variational Inequalities and Its Application to Lasso.
    Jun Liu, Zheng Zhao, Jie Wang, and Jieping Ye.
    ICML 2014.

  • Efficient Mixed-Norm Regularization: Algorithms and Safe Screening Methods.
    Jie Wang, Jun Liu, and Jieping Ye.
    arXiv:1307.4156v1

  • Lasso Screening Rules via Dual Polytope Projection.
    Jie Wang, Jiayu Zhou, and Peter Wonka, Jieping Ye.
    NIPS 2013. Spotlight

  • An Efficient ADMM Algorithm for Multidimensional Anisotropic Total Variation Regularization Problems.
    Sen Yang, Jie Wang, Wei Fan, Xiatian Zhang, Peter Wonka, and Jieping Ye.
    SIGKDD 2013.

  • VCells: Simple and Efficient Superpixels Using Edge-Weighted Centroidal Voronoi Tessellations.
    Jie Wang, and Xiaoqiang Wang.
    IEEE Transactions on Pattern Analysis and Machine Intelligence

  • Image Segmentation Using Local Variation and Edge-Weighted Centroidal Voronoi Tessellations.
    Jie Wang, Lili Ju, and Xiaoqiang Wang.
    IEEE Transactions on Image Processing

  • Edge-Weighted Centroidal Voronoi Tessellations.
    Jie Wang, and Xiaoqiang Wang.
    Numerical Mathematics: Theory, Methods and Applications

  • An Edge-Weighted Centroidal Voronoi Tessellation Model for Image Segmentation.
    Jie Wang, Lili Ju, and Xiaoqiang Wang
    IEEE Transactions on Image Processing

  • Evolutionary percolation model of stock market with variable agent number.
    Jie Wang, Chunxia Yang, Peiling Zhou, Yingdi Jin, Tao Zhou, and Binghong Wang.
    Physica A

  • Epidemic Spread in Weighted Scale-Free Networks.
    Gang Yan, Tao Zhou, Jie Wang, Zhongqian Fu, and Binghong Wang.
    Chinese Physics Letters